Over the past two decades, the promise of accelerated drug development and personalized medicine have brought heighten attention to the field of biomarker. But do you really know what biomarker are, how they are developed, and how they are used?
Here, I'll share over 15 years of experience in the fields of biomarker development and translational research to try to answer some of these questions.

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Sunday, October 30, 2011

The
Common Rule is the regulation governing research involving human subjects
(subpart A of 45 Code of Federal Regulation part 46). The original Common Rule was adopted in 1991
at a time when research was predominantly conducted at universities, colleges,
and medical institutions, and each study generally took place at only a single
site. The evolution of research involving
human subjects over the past two decades has revealed ambiguities in the
original regulations and has led to questions regarding the effectiveness of
the current regulatory framework to meet the needs of the researchers and
research subjects. On July 22 2011, the
department of Health and Human Services (HHS)
released an Advanced Notice of Proposed Rulemaking (ANPRM) for Revisions of the
Common Rule. This noticed was officially
published in the Federal Register on July 25th 2011 under the title:”Human
Subjects Research Protections: Enhancing Protections for Research Subjects and
Reducing Burden, Delay, and Ambiguity for Investigators“. Over the past 90 days, HHS has sought comment
on seven key issues (link):

Revising
the existing risk-based framework to more accurately calibrate the level
of review to the level of risk.

Using
a single Institutional Review Board review for all domestic sites of
multi-site studies.

Implementing
a systematic approach to the collection and analysis of data on
unanticipated problems and adverse events across all trials to harmonize the
complicated array of definitions and reporting requirements, and to make
the collection of data more efficient.

Extending
federal regulatory protections to apply to all research conducted at U.S.
institutions receiving funding from the Common Rule agencies.

Providing
uniform guidance on federal regulations.

As of
October 26th 2011, the 90-day period for public comment has been
closed.

In the
October 20th 2011 of Nature (link),
Krishanu Saha and J. Benjamin Hurlbut discuss these proposed changes to the
Common Rule in the context of biobanking. The authors argue that the revision
to the regulations does little, or even worsens, the current disconnect between
research subjects and researchers.
Indeed, the proposed changes to the Common Rule encourage the use of
blanket informed consent that in effect, ask donors to authorize all possible future
research unless they opt out of specific research categories (see also previous
post: Enabling
Retrospective Biomarker Studies: Resolving the Conflict between Short and Long
Term Goals). While this evolution of
the informed consent removes the ambiguity associated with the original Common
Rule (which resulted in legal disputes), according to the authors, it poses the
risk of reducing the involvement of the public in sample donation by further
distancing the research subjects from the research performed on their
samples. As a solution, the authors
advocate for a model in which the research subjects are actively involved. For example, disease advocacy groups have
succeeded in mobilizing research subjects by making them active players in the
prioritization of research activities. Companies like PatientsLikeMe and 23andMe
attract research subjects by providing feedback about and control over the research
conducted with volunteer samples.

The
idea of offering dynamic feedback about and control over research activities to
research subjects using for example, interactive web portals seems attractive
at first glance. Research subject could
decide in real-time to opt in or out of certain research activities. Researchers could easily gather supplemental
information about research subjects.
However, under this model, the rules of research subject anonymity
imposed by the Health Insurance Portability and Accountability Act (HIPAA)
would be substantially more difficult to maintain and would require considerably
stronger security measures to prevent accidental and/or malicious identification
of subjects. Also, the possibility of
providing to research subjects feedback about research activities would open
the door to the thorny issue of revealing unverified medical finding to the
subjects. Even if such communication were
to occur via the subject’s physician, the exploratory nature of the research precludes
the use of those findings for medical decision making. Actually, the company 23andMe has been under
increased scrutiny from the FDA Center for Devices and Radiological Health
(CDRH) for providing research-grade genetic information to their customers (see
earlier post: Genetic
biomarker: the power and risk of knowing), even though the company claims
that this information is not for medical decision making.

The
proposed changes the Common Rule provide a welcome clarification of the
regulations governing the collection and use of samples from human
subjects. While one can argue that these
changes are not ideal, it is also true that the original version of the Common
Rule exposed researchers and research subjects to a significant level of
ambiguity. Ultimately, the changes to
the Common Rule are designed serve the greater good for society by facilitating
medical research while preserving the right of research subjects.

Thierry Sornasse for Integrated Biomarker Strategy(The views expressed in this post are my own and are not meant to reflect the opinion of any other party)

Monday, October 24, 2011

In the
field of clinical biomarker research, it is common to need to explore new
hypotheses after the conclusion of a clinical study (i.e. retrospective
studies).However, if the proper samples
are not available, even the best ideas are no more than fantasies.While this statement might seem trivial, it
is surprising to discover that many bio / pharmaceutical companies struggle to implement
the proper strategic and tactical steps to enable retrospective
biomarker studies.

In my
experience, the most common strategic issue facing bio / pharmaceutical
companies in this area is in resolving the conflict between short term and long
term corporate goals.Specifically, in
the context of the conduct of clinical studies, the need to meet recruitment
quotas and deadlines often clashes with the proposal to acquire supplementary
samples that, at the time, have only theoretical value (i.e. potential use in
retrospective studies).Indeed, there is
a general consensus among the teams responsible for running clinical trials (i.e.
clinical operation) that adding sample collection procedures can complicate
approval of protocols by the Institutional Review Boards (responsible for clinical
study protocol approval on behalf of the institution and their patients) and
can impede patient recruitment.Therefore, unless there is a strong concrete justification for
collecting certain samples, additional sample collections tend to be excluded
from clinical protocols.The solution to
this apparent conflict resides in a strong corporate policy in support of
biomarker research in general and retrospective biomarker research in
particular.Without the assurance that the
logistical constrains imposed by sample acquisition for biomarker research will
be fully acknowledged as a factor affecting the conduct of clinical studies, clinical
operation will favor the bottom line (i.e. completion of studies in the
shortest possible time).

Beyond
a biomarker-friendly corporate attitude, the scientists and clinicians
responsible for biomarker research need to have a sound understanding of the
logistical impact of additional sample collection on clinical studies.Biomarker researchers need to be able to
negotiate intelligently with their colleagues in clinical operation.Reciprocally, clinical operation staff needs
to be with the scientific questions explored by the biomarker researchers.Therefore, cross-training of biomarker
researchers and clinical operation staff is one of the key aspects of a
successful clinical biomarker research program.

In
some cases, clinical samples that were collected for one purpose (e.g.
pharmacokinetics) can be repurposed for biomarker research.However, if the proper informed consent was not put in place at the time of sample
collection, using these samples for retrospective biomarker studies is not
acceptable.Indeed, current ethical and
legal standards mandate that all individuals enrolled in a clinical study be
fully informed about the use of the biological samples collected in course of
the study.The issue of drafting informed
consent forms that adequately inform the patients about future biomarker
research can be quite tricky.While it
is impossible to describe all potential future use of clinical samples for biomarker
research, it is important to define the overall intent and the limit of this
research.Also, it is often desirable to
draft the informed consent form with the option for the patient of opting in
(or out) of future biomarker research.

Finally,
assuming that clinical samples exist and are properly consented, efficient
retrospective biomarker research requires a solid sample management
system.Beyond the physical inventory of
samples, such as system ideally needs to seamlessly integrate anonymized
patient medical information, clinical study specific information, consent
status (whether patient opted in or out of biomarker research), and prior data
obtained from these samples.Hence, an
efficient patient sample management is as much about inventory management as it
is about information management.

Saturday, October 22, 2011

On
October 19th, the FDA Center for Devices and Radiation Health (CDRH)
released its Medical Device Pre-Market Programs: An Overview of FDA Actions (link).This document presents the center’s review of
the processes of pre-market approval of all medical devices, and articulates
solutions to the problems identified in this review.

First,
CDRH wants to dispel the misperception that safety/effectiveness and innovation
are incompatible.Their solution is not
to focus on whether more or less regulations are needed but rather to focus on
smart regulation: effectively achieve both aspects of the center’s mission as a
regulator and facilitator.

Second,
the number one problem identified from discussions with key stakeholders (i.e.
industry, academia, and payers) is insufficient predictability in the
pre-market program.This lack of clarity
has resulted in inefficiencies, increased cost for both the industry and the
FDA, and delays in bringing safe and effective innovative products to the
market.At the root of these problems,
CDRH identified excessive staff turnover, insufficient training (FDA and
industry), rapidly increasing workload associated with the growing complexity
and number of submissions, inconsistent data requirements, insufficient
guidance for the industry, and poor quality of industry submissions.

To address
these issues, CDRH is proposing a set actions centered on three areas of
emphasis:

Improving our ability to rely on data from outside the U.S.
and actions by regulatory bodies of other countries

For
regulatory purposes, diagnostics are medical devices.Therefore, the changes proposed by CDRH will
affect the submission and approval of novel diagnostics.Specifically, the development and approval of
diagnostics will most likely benefit from the improved review process with
greater predictability and transparency.The commitment of CDRH to actively interact with the sponsors will most
likely provide greater efficiency and reduced review time.The call for enrolling experts in the relevant
fields should streamline the process of defining the requirements for
successful submissions.

While
these improvements are promising, CDRH makes no secret that a significant
number of these solutions will require additional funding.The ongoing negotiations of the
reauthorization of user fees will therefore most likely result in higher cost
for the sponsors. In keeping with this
move, CDRH emphasizes the concept of shared responsibilities by stating: “We must fully embrace the paradigm
that assuring the safety and effectiveness of devices
is everyone’s job and the responsibility resides as much with industry,
practitioners and patients as with the Agency”.

The
specific aspect of review of approval of companion diagnostics is not
specifically addressed in this report.The sometime chaotic relationship between CDRH and its drug reviewing counterpart
CDER would certainly benefit from a similar review.

Tuesday, October 18, 2011

In the
October 17th issue of PLoS One, Robert Dawe and colleagues, from the
Illinois Institute of Technology and the Rush Alzheimer’s Disease Center, present
the results of a key bridging study of volumetric MRI correlation with normal
aging, Alzheimer’s disease (AD), and additional neuropathologies frequently
associated with aging (link).

As
mentioned in an earlier post (Biomarker
Qualification Consortia: The ADNI Success Story), in vivo volumetric MRI of
specific region of the brain (i.e. medial temporal lobe àhippocampus) has been shown
to be a valuable biomarker of disease progression in AD and mild cognitive
impairment (MCI). While the correlation
between reduction in hippocampal volume and histopathologically confirmed AD
has been conclusively demonstrated, the effect of other neuropathologies generally
associated with aging on hippocampal volume remained ill-defined.

In
order to address this gap in knowledge, the authors combined antemortem imaging
studies, antemortem cognitive testing, postmortem MRI on isolated brain
hemisphere, and histopathology on the brains of 100 elderly subjects from the
Rush Memory and Aging Project, and the Religious Order Study (two longitudinal
clinical-pathologic studies of aging). The
authors confirmed the strong association between reduced hippocampal volume and
the diagnostic of AD (determined prior to death based on cognition test and
determined postmortem based on histopathology).
In addition, hippocampal volume was related to multiple cognitive
abilities assessed proximate to death, with its strongest association with
episodic memory. Other pathologies such
as Lewy bodies, moderate amyloid
angiopathy, gross infarcts, and micro infarcts were not significantly associated
with reduced hippocampal volume. In
contrast, hippocampal
sclerosis (HS) was strongly associated with significant reduction in hippocampal
volume independently of the presence or absence of co-occurring AD pathology
(of 13 individuals with HS, 9 had also AD pathology and 4 had not other
pathology). In fact, the association of
HS and reduced hippocampal volume was more pronounced than that observed in AD.
Shape analysis of the hippocampal
surface confirmed prior knowledge namely that hippocampal volume reduction in
AD is more pronounced in the head and tail of the hippocampus, and that these
changes tend to be more homogeneously distributed in HS. The authors did not discuss whether shape analysis
of the hippocampal surface could be used to distinguish between AD and HS.

Despite
some minor limitations: the postmortem MRI performed on isolated brain
hemispheres precluded the measurement of cranial volume, this study provides a
highly valuable bridge between in vivo volumetric MRI measurements and
underlying neuropathology.

Thursday, October 13, 2011

In the
October 12th issue of PLos One, Alessia Lodi and Sabrina Ronen from
UCSF published the results of their work on the use of Magnetic Resonance Spectroscopy
(MRS)
to monitor the metabolic activity of tumor cells (link). Although this work was entirely conducted in
vitro on cell lines, the concept presented in this paper offer a glimpse at a possible
new approach to monitor drug effect early during treatment. Indeed, there is ample evidence that anti-cancer
drugs alter the metabolic profile of cancer cells before producing detectable
effects on tumor size (detectable by CT scan or MRI) or even
overall metabolic activity (detectable by FDG-PET).

The
utility of MRS to monitor early metabolic changes induced by drugs in cancer
cells has been demonstrated before.
However, these earlier studies focused on single metabolites which
limited their observations to the specific drug – cell combination studied. In this work, the authors expanded on earlier work
MRS use for the monitoring of cancer cell metabolism by used an unbiased 1H
MRS-based metabolomics approach to investigate the overall metabolic
consequences of treatment with the phosphoinositide 3-kinase inhibitor LY294002 and the heat shock
protein 90 inhibitor 17AAG in
prostate and breast cancer cell lines.

Obviously,
translating this concept to human patients, in which complexity will be several
orders of magnitude greater, will not be easy but one can speculate that as MRS
technology further progresses, tracking multiple metabolites in vivo will
become trivial.

This
week, the United States Preventive Services Task Force is due to release its draft
recommendation on the use of the Prostate-Specific Antigen (PSA) test in
healthy men of all ages. The PSA test
has been a standard tool in urology to assist in the diagnosis of prostate
cancer.

Essentially,
this recommendation states that the PSA test in healthy men has no
clinical benefit, does not save lives, and actually may lead to unnecessary
follow up tests and procedures that can have deleterious effects on the patient’s
health (see The New
York Times article).

These
conclusions are based on the results of five well-controlled clinical studies which
confirm the general empirical consensus about the PSA test: its lack of specificity
and sensitivity result in unacceptable numbers of false positive and false
negative tests, respectively. In
particular, false positive tests are particularly troublesome since a positive
test will usually lead to a biopsy and treatment that can lead to impotence
and/or incontinence. While those risks
of complications are somewhat acceptable for actual prostate cancer patients,
they are unacceptable for individual who have misdiagnosed.

This
recommendation by the United States Preventive Services Task Force is already
producing strong reactions from prostate cancer survivors and advocacy
groups. The idea of shelving the PSA
test is unacceptable to those who feel that this diagnostic saved their live. The truth is that neither the PSA test nor other
currently available tests are particularly useful in detecting prostate cancer. Hence, there is an urgent need to develop,
clinically validate, and deploy effective tools for the early detection of
prostate cancer in apparently healthy men.
Ironically, the dominance of the PSA test on the market has probably a substantial
obstacle to the development of new diagnostic in this field. Indeed, the protectionism from a segment of
the diagnostic industry with financial interest in PSA testing, as well as the difficulty
to change medical practices among physicians have probably contributed to the lack
of alternative prostate cancer diagnostics.
One can speculate that the new recommendation about PSA testing will
open a breach for innovative tools that will actually save lives.

Friday, October 7, 2011

In the
early online issue of the Proceedings of the National Academy of Sciences of
October 3rd (link),
Hu and colleagues reports on a new biomarker of disease activity for
Huntington’s disease (HD) based on the
differential expression level of the transcript for H2AFY gene
in peripheral blood mononuclear cells (PBMC). HD is an autosomal recessive genetic disorder in
which nerve cells in certain parts of the brain waste away, or degenerate.

Similarly
to the recent work on ALS biomarkers published in PLoS One this month (see
earlier post: New
Potential ALS Multiprotein Biomarker: Going Beyond Nerve Pathology), Hu et
al. hypothesized that the key pathobiology affecting neurons in HD would be
detectable in other cell types than neurons.
Indeed, the huntingtin protein, which has been shown to be at the center
of HD pathobiology, is expressed in most tissues, including PBMC.

Using
a standard transcriptomics approach, the authors surveyed the entire genome for
differential RNA expression between the PBMC of HD patients, healthy controls,
and other neurological disorders (Parkinson’s disease, Alzheimer’s disease,
corticobasal degeneration, essential tremor, progressive supranuclear palsy,
and multiple system atrophy). Using
stringent statistical criteria and pathobiological knowledge, the team selected
the transcriptional modulator H2A histone family member Y (H2AFY) as the most
relevant biomarker for HD. This initial
discovery was confirmed by two independent studies. First, a cross-sectional case controlled
study of an additional 36 HD patients, 9 carriers of the HD mutation with no
clinical symptoms (the HD mutation has 100% penetrance and therefore all
carriers will eventually develop the disease), 50 healthy controls, and one
individual with spinocerebellar ataxia.
Second, a longitudinal case-control study where 25 HD patients and 21
healthy controls were followed for at least 2 years (37 subjects were followed
for 3 years).

In order
to link the transcriptional difference observed in PBMC of HD patients to the
pathobiology of the disease, the authors analyzed the expression of the
H2AFY-encoded protein MacroH2A1
in the frontal cortex of postmortem brains obtained from 12 HD patients. While the expression of MacroH2A1 was clearly
elevated in the brain of patients with grade 2 or 3 disease, this trend was not
maintained in grade 4 patients. This was
most likely due to the fact that MacroH2A1 is expressed at high level in
neurons and that this stage of the disease is characterized by a substantial
loss of these cells. Finally, the authors assessed
the translational value of the H2AFY / MacroH2A1 biomarker in a mouse model of
HD (knock-in of exon 1 fragment of the human huntingtin gene). There again, the progression of the disease
was associated with an elevation of the MacroH2A1 protein in relevant brain
substructures and treatment with the experimental HDAC inhibitor sodium
phenylbutyrate resulted in a decrease in the biomarker signal.

Altogether,
if these observations are further confirmed, the availability of a disease
progression and a disease modification biomarker for HD should constitute a major
advance in the field. Indeed, the
development of drugs for the treatment of HD has been hampered by the lack of
sensitivity and precision of standard clinical end points. Similarly to other neurodegenerative diseases
such Alzheimer’s and Parkinson’s disease, clinical progression in HD is slow, erratic,
and relatively unpredictable at the individual level.

Beyond
the direct impact of this work, the approach used by Hu and colleagues seems to
signal a new trend in biomarker research: instead of limiting the scope of
biomarker research to the specific anatomical compartment primarily affected by
the disease, which in the case of the central nervous system is essentially
inaccessible, the field may significantly benefit from considering accessible
peripheral tissues which may display secondary pathobiology similar to that
affecting the primary tissues. Indeed, a
similar approach was used by Nardo and colleagues to identify a potential new protein
biomarker for Amyotrophic Lateral Sclerosis (PloS One October 5th; see
earlier post: New
Potential ALS Multiprotein Biomarker: Going Beyond Nerve Pathology)

Thursday, October 6, 2011

In the
October 5th issue of PLos One, Nardo and colleagues (link)
present the results of their work on a new peripheral blood cell-bases biomarker
for the diagnosis and monitoring of Amyotrophic Lateral Sclerosis (ALS: a disease
of the nerve cells in the brain and spinal cord that control voluntary muscle
movement).

Based
on the assumption that ALS pathobiology is no restricted to the nervous system,
the authors conducted a classic proteomics analysis (2D-DIGE)
of pooled peripheral blood mononuclear cells (PBMC) collected from healthy
controls and patients suffering from ALS (grouped into two disease severity
cohorts based on the ALS functional rating scale revised [ALSFRS-R]). The first set of 71 candidate biomarkers was first
refined to a 14-protein biomarker panel by validation against healthy
controls. This subset was further
refined to a 5-protein ALS-specific biomarker panel (table 1) by validation
against other neurological disease controls that may clinically resemble ALS.

Table 1

Out of
this 5-protein panel, the combination of IRAK4 and CypA was the most associated
with ALS versus other neurological disorders, yielding a discriminatory power
of 91% at the appropriate cut-off value (Receiver Operator Curve AUC = 0.905).

From
the original 14-protein biomarker panel, the authors also derived a 3-protein
ALS severity biomarker panel (table 2) by comparing patient samples from
moderate disease (ALSFRS-R > 24) to samples from patients with severe
disease (ALSFRS ≤ 24). Out of this 3-protein panel, ERp57 was the
most associated with disease severity with 89% discriminatory power at the
appropriate cut-off level (Receiver Operator Curve AUC = 0.893).

Table 2

Finally,
the authors investigated the translational value of the 14-protein biomarker
panel by analyzing those proteins in the PBMC and the spinal cord from a rat
model of ALS (G93A SOD1-transgenic rats).

By
showing that disease biomarkers for a neurological disease can be identified in
easily obtainable PBMC, this work represents an important step in the evolution
of biomarker research. Instead of
limiting the scope of biomarker research to the specific anatomical compartment
primarily affected by the disease, which in the case of the central nervous
system is essentially inaccessible, the field may significantly benefit from considering
accessible peripheral tissues which may display secondary pathobiology similar
to that affecting the primary tissues.

Wednesday, October 5, 2011

In the
October 4th issue of Plos One, Wardlaw and colleagues published the
results of a survey about the public and the expert perception of neuroimaging use
in society (link).This fascinating societal insight in the
current and future use of neuroimaging highlights an often overlook aspect of
biomarker and diagnostic research: the potential adoption barrier caused by conflicting
information propagated by the general media.Indeed, the development of some new, or even established, technologies can be
thwarted by excessive regulations stemming from unwarranted fears propagated by
a media industry hungry for sensational sound bites.

In
this case, the authors focused on assessing the opinions of the general public
and of medical experts on the medical and non-medical use of neuroimaging in
modern society.In particular, the authors
sought to gather opinions about the claim that modern neuroimaging can be used
for detecting lies in a judicial context, preferences in a marketing context,
and racial attitude in a social context.

While
the public and the experts all agreed that conventional medical uses of neuroimaging
(i.e. detection of brain pathology and certain mental illness) are trustworthy
and well established, both groups showed little faith in uses of neuroimaging
in non-medical applications.However,
the survey revealed that the experts had little awareness of the use of neuroimaging
in US court, grossly underestimating the number of cases where neuroimaging have
been used as evidence over the past few years.Similarly, a third of the experts reported no familiarity with the use
of neuroimaging in the fields of neuromarkerting and commercial lie-detection.Interestingly, although the majority of
experts felt that the actual state of neuroimaging was not accurately
represented by the general media, few felt compelled to rectify the situation.

Looking
ahead, the experts were generally more optimistic about the future of
neuroimaging than the general public.While
the relative skepticism from the public may provide some degree of protection
against the misrepresentation of neuroimaging capabilities by the general
media, the relative enthusiasm of the experts means that there is no shortage
of expert opinions that can be used out of context by the general media to
promote sensational claims about neuroimaging capabilities.

Although
this paper does not intend to address the entire field of biomarker and
diagnostic development, these findings should serve as a lesson for the entire field.Consistent communication about the true capabilities
of a new biomarker / diagnostic technology should be an integral part of the
final stage of diagnostic development.Failing to do so could result in the public misperception of the
advantage and/or risk of a new promising technology.

Tuesday, October 4, 2011

In an
earlier post Biomarker
Qualification Consortia: The ADNI Success Story, I discussed the value of
biomarker qualification consortia by highlighting the success of the NIH
sponsored Alzheimer’s Disease Neuroimaging Initiative (ADNI).
Here, I would like to raise awareness to another biomarker qualification
consortium in the field of neurodegenerative medicine: the Michael J. Fox
Foundation sponsored Parkinson Progression Marker Initiative (PPMI).

PPMI
is a consortium of academic, industrial, and non-profit organizations dedicated
to the assessment and qualification of biomarkers of Parkinson’s disease (PD)
through the longitudinal monitoring of early PD patients. In contrast to ADNI, PPMI main sponsor is the
Michael J. Fox Foundation: a non-profit organization dedicated to the
advancement of PD treatment through scientific research and public awareness. PPMI has assembled a total of 21 sites in the
US and Europe which will recruit and follow 400 early PD patients and 200 age-matched
controls volunteers over a 5-year period.
Similarly to ADNI, PPMI has defined a set of standardized protocols for
the assessment of clinical (motor assessment, neuropsychiatric, olfaction) end
points and imaging (DATScan,
MRI, DTI),
biochemical (alpha-synuclein,
DJ-1, urate), and genetic
biomarkers. In keeping with the non-competitive
spirit of the consortium, all data collected by PPMI will be made available to
the scientific community through a centralized data repository. PPMI also intends to facilitate access the
biosamples collected from the study participants.

Although
PPMI has only been active since June 2010 and not all sites have been active
since the study start, the study has already enrolled 50% of the control
participants (goal: 200 individuals) and 31% of the PD participants (goal: 400
individuals).

As it
is common for studies of this magnitude, PPMI has encountered a few bumps in
the road. Although DATScan was approved by
the FDA for US use on January 14th 2011, this critical imaging
biomarker technology has not been available since February 2011 (status may
have changed since this information was released).

On
September 29th, Siemens announced that the company had completed a
phase II study of their new tumor hypoxia Positron Emission Tomography tracer
HX4 (link).The ability to identify hypoxic tumors through
imaging is of great significance to the personalized management of a broad variety
of cancers since hypoxic tumors tend to be more resistant to radiotherapy and
chemotherapy.

HX4 is
not the first PET tracer developed as a biomarker of tumor hypoxia.For instance, F-MISO ([18F]‑Fluoromisonidazole)
has been tested with some success in the clinic (reference)
but its relatively slow rate of clearance from the body have limited the
utility of this tracer (link).In contrast, HX4 has demonstrated a faster
clearance from the body while maintaining a reproducible uptake by hypoxic
tumors, producing higher image contrast within a relatively short period
post-injection (i.e. 145 minutes).

Of
note, HX4 has not yet been approved but is intended for world-wide distribution
by PETNET Solutions, a wholly owned Siemens subsidiary which already provides
PET tracers such as [18F]FDG and Na[18F] for metabolic
uptake and bone metastasis imaging, respectively.

Thursday, September 29, 2011

Transport
yourself 10 to 15 years from now and try to imagine what the future of
personalized medicine will look like.
The vision of every drug prescription decisions being driven by a test
aimed at tailoring the treatment to a particular individual is probably
utopian. Rather, I would argue that the
realm of personalized medicine will still be limited to the treatment of severe
and/or life-threatening diseases that require expensive medications. Under this premise, what are the forces that
will shape the future of personalized medicine?

In my
mind, this question can be addressed by considering the field from a supply and
demand perspective. On the supply end, the
pharmaceutical and diagnostics industries will remain the main forces driving the
future of personalized medicine. The imperative
of improving the return on investment in drug development will dominate the
future of the pharmaceutical industry. With
the era of relying mainly on “one-size-fit-all” drugs fading away, the focus will
shift towards precision/personalized medicine where drugs are designed to
address the need of smaller targeted patient populations. Hence, the need to develop the tools that
will identify the right patient population (for efficacy and/or safety reasons)
will constitute a major theme in drug development. This does not exclude the continuing effort
of the pharmaceutical industry to develop and commercialize broadly applicable
drugs for the management and/or treatment of conditions for which a
personalized approach is not warranted (for cost-benefit and/or clinical
utility reasons). Still on the supply
end but with an eye on the demand side, the regulatory authorities will
continue to play a major role in the harmonization of the biomarker and
companion diagnostic development process. Beyond the current regulatory framework
governing the regulatory approval of drugs and companion diagnostics, the
regulators have been working on developing a new process for an integrated
development of biomarkers intended to become companion diagnostics (see earlier
posts: Harmonization
of Biomarker Qualification Regulatory Submissions; Companion
In Vitro Diagnostics (IVD) Development).

Probably
the most significant force that will shape the future of personalized medicine
will be on the demand side, represented by the patients, the medical
practitioners, and most importantly the health insurance/payers. For all three entities, the adoption of a new
companion diagnostic will require proof of clinical utility (Ref1,
Ref2,
& Ref3). In a nutshell, clinical utility for a molecular
diagnostics is the third level of a three-tiered evaluation framework that
includes “analytical validity”, “clinical validity/qualification”, and
“clinical utility” (Ref2).
Hence, clinical utility encompasses the overall
medical impact of a diagnostic. A
diagnostic is considered clinically useful if it provides a real and
substantial advantage to the patients, positively alters the practice of
medicine, and/or improves the cost / benefit equation for a given
treatment. Although clinical utility is
a distinct concept from analytical and clinical validity, it cannot be
established without first establishing the latter. The reciprocal is however not true:
establishing analytical and clinical validity does not imply proof of clinical
utility.

While the
pharmaceutical industry and the regulators are currently focusing most of their
efforts on defining and implementing the rules of diagnostics analytical and
clinical validation, I would argue that the next decade will be dedicated to the
third part of the equation: defining and implementing the rules of diagnostics clinical
utility evaluation.

Friday, September 23, 2011

In the
September 21st issue of Science Translational Medicine (link), scientists at Genentech
reveal their findings about a new, clinically qualified biomarker of
non-response to antibody therapy to CD20 in rheumatoid arthritis (RA). B cell depleting therapy using the anti-CD20
mAb rituximab in RA (link) is reserved for patients who
have failed standard disease-modifying antirheumatic drugs (specifically
methotrexate) and/or with inadequate response to anti-TNF antibody
therapy. Considering the cost,
complexity, and relative risk associates with anti-CD20 therapy and considering
that about 50% of RA patients do not respond to rituximab, there is a strong
impetus to target this therapy to patients who are most likely to respond
favorably.

Hypothesizing
that RA patients with high frequency of antibody producing plasma B cells are
less likely to respond to rituximab (plasma cells do not express CD20), the
team at Genentech surveyed a set of B cell and plasma cell specific RNA
transcripts in blood samples from a subgroup of patients who had been treated
with rituximab (REFLEX study). Using the American College of Rheumatology
50% improvement criteria (ACR50), they identified a clear association between
failure to meet ACR50 and elevated levels of RNA for the immunoglobulin J chain
(IgJ) at baseline. They confirmed this observation using blood
samples from patients enrolled in two additional independent rituximab studies
(DANCER and SERENE), and one study of ocrelizumab
(a second generation anti-CD20 mAb) in RA (SCRIPT). When all four trials were combined, the ACR50
response rate in the active arms was 28% for the IgJlo group (n =
471) and 12% for the IgJhi group (n = 122) (Odd ratio: 2.7; 95%
confidence interval: 1.5 to 5.3). The
predictive power of the IgJ RNA level was further refined by combining this
parameter with the RNA levels for the B cell specific splice variant of Fc
Receptor-like 5 (FCRL5). Together, elevated levels of IgJ RNA and low
levels of FCRL5 at baseline (biomarker positive: IgJlo / FCRL5hi)
were strongly associated with low probability of positive response to anti-CD20
mAbs therapy (figure 1). Indeed, in the
combined 4 clinical studies, 28% of biomarker-negative patients responded to
treatment while only 9% of biomarker positive patients responded under the same
conditions (Odd ratio: 3.6; 95% confidence interval: 1.8 to 8.4). Of note, this combination biomarker does not
appear to be an indicator of more severe diseases since it was not associated
with different response rate in the placebo groups from those clinical studies.

Fig. 1

Beyond
representing a major advance in the area of treatment decision in RA
patients, this work represents a remarkable example of the power of well-planned, well-executed prospective
retrospective studies for the discovery and clinical qualification of novel
biomarkers

Thursday, September 22, 2011

In the
early online issue of September 22nd of BMC Medicine (link;
provisional paper), Philip Schuetz, Werner Albrich, and Beat Mueller review the present and the future promises of procalcitonin (PCT) as a potential generalized biomarker
of infection and potential guide to antibiotic prescription in clinical
settings. As the authors point out, the
field currently lacks reliable biomarkers of bacterial infection that can be assessed
rapidly from easily accessible samples, resulting in suboptimal management of antibiotics
administration. Therefore, beyond the
direct benefit of expediting the diagnosis of bacterial infection, PCT could be
used to develop an antibiotic prescription algorithm that would potentially
optimize antibiotics usage by eliminating their use in circumstances where they
are not needed (fig. 1)

While strong
evidences from randomized clinical trials support the use of PCT to guide the
prescription of antibiotics for the treatment of lower respiratory tract infections
(upper respiratory tract infection, pneumonia, COPD exacerbation, and acute
bronchitis), and severe sepsis, more work needs to be done to establish PCT as
a clinically relevant tool in the management of infections such as bacteremia,
abdominal infection, neutropenia, and postoperative fever.

Friday, September 16, 2011

A
press release on September 16th on Market Watch about KineMed caught
my attention (link). KineMed, based in Emeryville CA, has developed
new proteomics and metabolomics tools that enable the monitoring of metabolic
flux through complex biological pathways by exploiting the power of deuterated
water (or heavy water: 2H2O) labeling. By monitoring the kinetic of predictable mass
shift of molecules of interest by mass spectrometry, the scientists at KineMed
have been able to ascertain complex dynamic processes such as blood clotting,
complement cascade activation, epidermal turnover in psoriasis patients, anterograde
neuronal transport in ALS and PD patients, and
DNA turnover rate in leukemia and breast cancer (see a video
presentation by Marc K. Hellerstein, M.D., Ph.D.; co-founder of KineMed)

Because
of its non-radioactive nature and ease of deployment (deuterated water is
simply administered as a glass of water), this technique offers the prospect of
identifying new biomarkers related to disease processes, drug mechanism of
action, and drug toxicities. It is
important to remember though that this technique does not allow for in situ
metabolism monitoring and thus still requires sample collection. Therefore, the usual limitations associated
with the collection of biosamples do apply to this new technique.

In the
August 24th early online issue of Drug Discovery Today (reference),
Michael Nohaile from Novartis Pharma AG discusses the key factors required to
translate a promising biomarkers into an effective companion diagnostic (CDx). Based on a pragmatic staging scheme of drug –
CDx co-development (figure 1), the author dissects the complex cross-functional
interactions between of analytical and clinical validation, regulatory affairs,
and intellectual property management.

Fig.1

On the
analytical validation front, the author stresses the importance of timely assay
platform selection, the need for proper consideration of pre-analytical
parameters (see my earlier post: Biomarker
Research: The Pre-analytical Puzzle), and the critical issue of the synchronization
of the assay validation process to meet clinical development milestones. Failure to complete assay validation before
the initiation of pivotal clinical will require the conduct of complex and
expensive bridging studies to satisfy the regulatory requirement for CDx.

On the
clinical validation front, the author discusses the issue of adequate sample ascertainment
rate from clinical studies in the context of prospective-retrospective (predefined
analysis of samples from a completed study) CDx clinical validation strategies,
and the issue of the statistical power for purely prospective CDx clinical
validation studies. In particular,
serious consideration should be given to the decision of including or excluding
marker negative patients in such studies.
On the one hand, inclusion of marker-negative patients is required to
determine the positive and negative predictive value of the candidate CDx. On the other hand, beyond being less
expensive and potentially faster, studies that exclude marker-negative patients
may also present an ethical advantage in cases where the potential treatment benefit
is expected to be negligible in marker-negative individuals.

From a
regulatory affairs perspective, the fact that CDx are regulated by the Center
for Devices and Radiological Health (CDRH) implies that specific regulatory
expertise is required for the successful prosecution of CDx (see also my
earlier post about recent FDA guidance:
Companion In Vitro Diagnostics (IVD) Development: some clarity at last). In particular, the fact that the risk /
benefit analysis for CDx is entirely tied to the risk / benefit profile of the
associated drug implies a close collaboration between the drug reviewing
authorities (CDER/ CBER) and the device reviewing authorities (CDRH).

Finally,
from an intellectual property, the author discusses the issue of the timing of patent
filing and the more global issue of patentability of biomarkers.

Thursday, September 15, 2011

In the
September 13th issue of PLoS One (link),
John D. Storey and colleagues report on inflammation-related gene expression signatures
associated with differential clinical outcome in acute trauma patients. Specifically, the authors analyzed the
expression of inflammation-related genes in 168 blunt-force trauma patients over
a 28-day period. The genes and gene
pathways that clustered differently between patients’ clinical outcome subgroups
(based on Marshall multiple
organ failure clinical score) were assembled into predictive modules of
clinical outcomes. Of particularly
interest, the down-regulation of MHC II expression within 48 hours of trauma and
up-regulation of p38-MAPK within 100 hours of trauma were particularly robust independent
predictors of negative clinical outcome in this patient sample.

Considering
that up to 60% of late trauma mortality is caused by infections, sepsis, and
multiple organ failure multiple organ, the management of these
inflammation-related complications remains a major unmet medical need. In particular, the ability to predict the
individual patient clinical trajectory early during trauma treatment remains a
significant challenge for the medical community. Therefore, the prospect of using gene
expression as a prognostic biomarker to manage the care of trauma patients is
of particular significance.

Our
perception of biomarkers tends to be limited to the realm of measures that
provide information about disease and drug activity. In fact, biomarkers can provide a means to
assess additional biological processes relevant to patient well being such as
anxiety and pain. In paper published in
the September 13th issue of PLoS One (link),
a team of the Department of Anesthesia, Stanford University describes a new functional
MRI-based (fMRI) biomarker for the identification of pain. Because the sensation of pain can be
subjective and can occur in the absence of detectable injury, the standard for
assessing pain is based on patient self report.
While this traditional measure is readily assessable, it does not
differentiate between the sensory and the psychological components of pain
perception. In addition, patient self
reported pain assessment is impossible in individuals who are not able to
communicate. Therefore, development of
an objective biomarker of pain is of great interest to the medical
community.

The
team at Stanford performed a pilot study involving 24 individuals who were
monitored by fMRI while being subjected to painful and non-painful thermal
stimuli. Using the results from the first
8 volunteers, the team used Support Vector Machine learning to develop a predictive
model that then validated on the remaining 16 individual volunteers. In this setting, the model accurately
identified the type of stimulus with 81 % accuracy.

While
the size of this study is not sufficient to draw definitive conclusions, it is
tempting to speculate that the future of pain management in patients who are
unable to communicate may improve dramatically

Monday, September 12, 2011

In the
September 2011 issue of the Archives of General Psychiatry (reference),
Dr. Goldberg and colleagues report the results of the first study that examined
the respective predictive values of cognitive measures, brain imaging, and
cerebrospinal fluid (CSF)
biomarkers in determining the risk of conversion from Mild Cognitive Impairment
(MCI) to
Alzheimer’s disease (AD).

In
contrast with the multiple recent publications derived from the Alzheimer’s
Disease Neuroimaging Initiative about biomarkers in AD (ADNI; see
earlier post), this work identified measures of delayed verbal memory (Logical
Memory delayed recall and Auditory Verbal Learning Test delayed recall) as the
most reliable predictors of progression from MCI to AD. While brain volume assessed by MRI (Left
middle temporal lobe thickness) was identified as an additional predictive
factor, the levels of Ab42 and Tau in the CSF did not add significant
predictive value to their model (systematic stepwise logistic regression).

In
commentary provided to Medscape (link), the lead author urged
caution in interpreting this finding by stating that “Biomarkers unarguably
work. However, cognitive markers, which are less expensive and less invasive,
also work and provide strong complementary information”.

In my
mind, the question is not so much whether cognitive assessment tools work
better than CSF biomarkers but more about the applicability of these findings
to the general practice of medicine.
Indeed, while CSF biomarkers are objective measures, the results of even
the best cognitive tests are partially subjective: the skills of the person
administering the test can have an influence on the results. Therefore, one can wonder if, in the hands of
the average neurologist or neuropsychiatrist, the verbal
memory testing would perform as well and would outperform the objective measure
provided by CSF biomarkers.

Friday, September 2, 2011

The list of pharmacogenomic biomarkers included the labels of FDA approved drugs has grown substantially over the last 10 years. The most recent update from the FDA (Table of Pharmacogenomic Biomarkers in Drug Labels; 08/25/2011) lists 109 pharmacogenomic biomarkers included in the labels of 97 drugs (the labels of some drugs such as Imatinib and Warfarin include more than one pharmacogenomic biomarkers).

From a regulatory perspective, these biomarkers can be included in different sections of the drug labels (e.g. box warning, contraindication, clinical pharmacology), informing the prescribing physicians and the patients about identification of responders / non-responders, avoiding adverse events, and optimizing drug dosage. The label information about pharmacogenomic biomarker can describe:

Drug exposure and clinical response variability

Risk for adverse events

Genotype-specific dosing

Mechanisms of drug action

Polymorphic drug target and disposition genes

Functionally, the majority of the pharmacogenomic biomarkers currently included in the label of approved drug fall into the category of safety and efficacy markers related to drug exposure due to altered drug metabolism. Indeed, 60 of the 109 pharmacogenomic biomarkers belong to the liver cytochrome P450 enzymes (CYP) which play a critical role in drug metabolism. Other functional variants of enzymes involved in drug metabolism such as dihydropyrimidine dehydrogenase (DPD) and thiopurine S-methyltransferase (TPMT) also fall into this category.

Although still representing a minority of cases, the number of drug efficacy pharmacogenomic biomarkers included in cancer drug labels has been growing (i.e. response biomarkers, predictive biomarkers). In general, these biomarkers are designed to assist in the prescription decision by testing for the presence of the drug target.

Examples:

Imatinib: C-kit, BCR-Abl, PDGFR

Trastuzumab: Her2/neu

Vemurafenib: BRAF

Tositumomab: CD20

As the field of biomarker development in support of drug development evolves, it is expected that this list of pharmacogenomic biomarkers included in drug labels will grow substantially, making the promise of personalized medicine a reality.

In the September 1st issue of Lab on a Chip, Wang and colleagues report a proof-of-concept for an easily deployable, point-of-care diagnostic system for the detection of the ovarian cancer HE4 biomarker (reference). The team combined a simple microchip-based ELISA platform with the imaging capability of modern portable phones. Interestingly, the performances (sensitivity and specificity) of the portable phone camera appeared to be superior to a stand-alone CCD camera.

Although this work may seem anecdotal at first glance, it constitutes a valuable step towards increased diagnostic accessibility through the translation of a standard “high-tech” laboratory method to a “low-tech” broadly deployable platform.

Thursday, September 1, 2011

In the September 1st issue of Biomedical Optics Express (reference), Zheng and colleagues present a proof of concept study for a novel type of biosensor for the detection of proteins in blood. Briefly, the team immobilized amine-terminated aptamers – artificial oligonucleotides engineered to bind specific ligands – onto a gold modified surface and used Surface Plasmon Resonance (SPR) to detect the binding of the ligand; in this case thrombin. This prototype sensor showed good performances (sensitivity, linearity, and reversibility) for the intended ligand (thrombin), in the presence or absence of high levels (400 nM) of BSA, suggesting that this technology could be applied to direct detection of reasonably abundant factors in blood.

Considering the relative inexpensive nature of the manufacturing process of this new biosensor and the relative simplicity of SPR detection, it is tempting to speculate that this technology could solve the issue of cost for current and new blood diagnostics. Time will tell if the reported performance of this prototype biosensor will be reproduced for other blood proteins.

In the September 1st issue of Nature (reference), scientists from the Helmholtz Zentrum Munchen Institute in Munich, Germany, the Wellcome Trust/Sanger Centre, King’s College, and Metabolon, Inc. present the most comprehensive Genome Wide Association Study (GWAS) aimed at identifying relationship between individual genetic variations and specific metabolic pathways. Using ultra-high performance LC-MS and GC-MS, the levels of over 250 metabolites, representing over 60 metabolic pathways, were analyzed in serum samples from volunteers enrolled in the German KORA F4 study (n= 1768) and in the British TwinsUK study (n= 1052). From these measures, over 37,000 metabolic traits (concentrations or ratios of metabolite pairs) were derived and their association with about 600,000 SNPs was assessed. The team identified 37 independent genetic loci with genome-wide significant associations with metabolic traits, 23 of which represented novel associations. Moreover, among these 37 genetic loci, 15 overlapped with known disease-associated genetic loci, shedding new light on possible new pathobiological mechanisms of diseases such as diabetes, kidney failure, venous thromboembolism, and coronary artery disease.

This remarkable work represents a major evolution in the field of GWAS by providing a means to place genetic information within a functional biological context. Indeed, despite identifying thousands of disease risk loci, most GWAS are cataloging exercises offering little or no information about the biological processes potentially associated with the identified genetic variants.

Wednesday, August 31, 2011

In the August 30th issue of PLoS One, Fuchikami and colleagues report their findings about a new biomarker of severe depression based on Brain-Derived Neurotrophic Factor (BDNF) gene methylation profiles (reference). Briefly, the authors analyzed the methylation profile of the BDNF gene in blood samples collected from 20 clinically diagnosed severe depression patients and 18 healthy human volunteers (see figure 1). Their analysis covered 81 CpG units upstream of exon 1 (CpG I) and 28 CpG units upstream of exon 4 (CpG IV) of the BDNF gene. Differential methylation status in CpG I appeared markedly different between patients and controls, with an overall trend for hypo-methylation in patients with major depression. The biological implication of this methylation profile is currently unknown.

Fig.1

Considering the small sample size used in this study, these findings should be viewed as an initial screening for potential biomarker candidates which will require substantially more work to be confirmed. First, because the individuals enrolled in this first study were exclusively of Japanese origin, the relevance of BDNG gene methylation status as a biomarker of depression remains to be established in a more ethnically diverse population. Second, as I have mentioned in an earlier post (link), the reductionist sample selection process used in this study probably yielded over-optimistic statistical association values that may not translate well to the more complex real-world. Indeed, the diagnosis of major depression is almost never made as a simple binary determination of “healthy” vs. “depressed”. Rather, the diagnosis of depression is a process of eliminating other conditions that manifest themselves with similar symptoms. Hence, analysis of the BDNF gene methylation profile in clinically related psychiatric conditions should constitute an important follow up to this initial study. Finally, assuming that these biomarker candidates are confirmed, it would be particularly interesting to determine whether current treatments for depression affect the methylation profile of the BDNF gene.

Of note, it seems that the field of biomarker discovery in the area of depression is picking up speed lately. This paper comes one day after the announcement by Lundbeck Canada of a $2.7 million donation in support of biomarker discovery in the area of major depression and bipolar disorder (announcement), and a few weeks after the cover story of Ridge Diagnostics’ depression blood test in the August issue of Psychiatric Time (see earlier post).